Our experiments are conducted on the MSPPodcast[1]} and IEMOCAP [2]}. MSP Podcast is the largest human labelled emotion dataset with 29,965 training examples and 10,013 test utterances. It is comprised of segments of speech from podcasts, which means that the speech is expressive and the acoustic environment less constrained by background noise and other interference. The MSPPodcast data has labels for three continuous dimensions - valence, arousal and dominance, and for multiple discrete emotions - of which we use five : neutral, angry, happy, sad, and disgust. In this work, we report our results on the balanced test1 evaluation set with 30 male and 30 female speakers.
The second dataset we use is IEMOCAP which is a 20 hour dataset, with annotations on acted emotion. It comprises of 10 different speakers, 5 male and 5 female. It is labelled for three continuous dimensions - valence, arousal and dominance, and for 9 discrete emotions out of which we utilise the ones that overlap with our MSPPodcast set, i.e., neutral, angry, happy, sad, and disgust.
